Fault detection in the marine engine using a support vector data description method

Klaudia Wrzask; Jerzy Kowalski; Van Vang Le; Van Bac Nguyen; Dao Nam Cao

doi:10.1080/20464177.2024.2318844

Fault detection in the marine engine using a support vector data description method

Abstrakt

Fast detection and correct diagnosis of any engine condition changes are essential elements of safety andenvironmental protection. Many diagnostic algorithms significantly improve the detection of malfunctions.Studies on diagnostic methods are rarely reported and even less implemented in the marine engine industry.To fill this gap, this paper presents the Support Vector Data Description (SVDD) method as applied to thefault detection of the fuel delivery system of a two-stroke marine engine. The selected diagnostic data is theexhaust gas composition, with four components considered: oxygen, carbon oxide, nitric oxide, and carbondioxide. With these diagnostics, the method distinguishes eight different engine faults from the efficient state.The manuscript presents in detail the methodology for applying the SVDD method in a marine engine. Themethod of obtaining diagnostic data and its scaling is described. The method of training and validating thealgorithm is also presented, along with ready-made algorithms for use. The 100% accuracy of the proposedfault detection method. Based on the obtained results, the proposed fault detection method is promising fora simple application. Moreover, generalised algorithms that may be adapted to different technical solutionsare also presented.

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Autorzy (5)

Klaudia Wrzask dr inż.
Jerzy Kowalski dr hab. inż.
Van Vang Le
- Institute of Maritime, Ho Chi Minh City University of Transport, Ho ChiMinh City, Viet Nam
Van Bac Nguyen Dr
- Institute of Engineering, HUTECH University, Ho Chi Minh City, Viet Nam
Dao Nam Cao
- PATET Research Group, Ho Chi Minh City University ofTransport, Ho Chi Minh City, Viet Nam

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Kategoria:

Publikacja w czasopiśmie

Typ:

artykuły w czasopismach

Opublikowano w:

Journal of Marine Engineering and Technology strony 1 - 11,
ISSN: 2046-4177

Język:

angielski

Rok wydania:

2024

Opis bibliograficzny:

Wrzask K., Kowalski J., Le V. V., Nguyen V. B., Cao D. N.: Fault detection in the marine engine using a support vector data description method// Journal of Marine Engineering and Technology -, (2024), s.1-11

DOI: